Intensive Longitudinal Assessment of Adolescents to Predict Suicidal Thoughts and Behaviors

Abstract

Objective: Suicide is a leading cause of death among adolescents. However, there are no clinical tools to detect proximal risk for suicide.

Method: Participants included 13- to 18-year-old adolescents (N = 103) reporting a current depressive, anxiety, and/or substance use disorder who owned a smartphone; 62% reported current suicidal ideation, with 25% indicating a past-year attempt. At baseline, participants were administered clinical interviews to assess lifetime disorders and suicidal thoughts and behaviors (STBs). Self-reports assessing symptoms and suicide risk factors also were obtained. In addition, the Effortless Assessment of Risk States (EARS) app was installed on adolescent smartphones to acquire daily mood and weekly suicidal ideation severity during the 6-month follow-up period. Adolescents completed STB and psychiatric service use interviews at the 1-, 3-, and 6-month follow-up assessments.

Results: K-means clustering based on aggregates of weekly suicidal ideation scores resulted in a 3-group solution reflecting high-risk (n = 26), medium-risk (n = 47), and low-risk (n = 30) groups. Of the high-risk group, 58% reported suicidal events (ie, suicide attempts, psychiatric hospitalizations, emergency department visits, ideation severity requiring an intervention) during the 6-month follow-up period. For participants in the high-risk and medium-risk groups (n = 73), mood disturbances in the preceding 7 days predicted clinically significant ideation, with a 1-SD decrease in mood doubling participants' likelihood of reporting clinically significant ideation on a given week.

Conclusion: Intensive longitudinal assessment through use of personal smartphones offers a feasible method to assess variability in adolescents' emotional experiences and suicide risk. Translating these tools into clinical practice may help to reduce the needless loss of life among adolescents.

Keywords: cluster analysis; daily diary; digital phenotyping; suicidal ideation; suicide attempts.

Figure 1.

K-Means Clusters, Average Mood, and Mood Variability (A) K-means clusters based on weekly ratings of suicidal ideation severity over the 6-month follow-up resulted in a 3-cluster solution: (a) High-Risk (Cluster 3; Blue): higher overall mean, max rating, percentage of weeks reporting ideation, and greater week-to-week variability, (b) Medium-Risk (Cluster 1; Red): moderate mean, max, percentage of weeks reporting ideation, and week-to-week variability, and (c) Low-Risk (Cluster 2; Green): low mean, low variability and low frequency and variability of suicidal ideation. Mean = Average weekly suicide ideation; Max = maximum suicide ideation rating over the 6-month follow-up period; PCT = Percentage of weeks reporting suicide ideation (i.e., >1); RMSSD = root mean square of successive difference. (B) Plot of weekly average mood (x-axis) and weekly RMSSD of mood (y-axis) for the Low- (Green), Medium- (Red), and High-Risk (Blue) groups; highlighting both lower mood for the High-Risk group and greater variability for the Medium Risk group.